Human Action Recognition Based on Radon Transform

UTSePress Research/Manakin Repository

Search UTSePress Research


Advanced Search

Browse

My Account

Show simple item record

dc.contributor.author Chen, Yan en_US
dc.contributor.author Wu, Qiang en_US
dc.contributor.author He, Sean en_US
dc.contributor.editor Weisi Lin, Dacheng Tao, Janusz Kacprzyk, Zhu Li, Ebroul Izquierdo, and Haohong Wang en_US
dc.date.accessioned 2012-10-12T03:31:31Z
dc.date.available 2012-10-12T03:31:31Z
dc.date.issued 2011 en_US
dc.identifier 2011002116 en_US
dc.identifier.citation Chen Yan, Wu Qiang, and He Xiangjian 2011, 'Human Action Recognition Based on Radon Transform', Springer-Verlag Berlin / Heidelberg, Berlin/Heidelberg, pp. 369-389. en_US
dc.identifier.issn 978-3-642-19550-1 en_US
dc.identifier.other B1 en_US
dc.identifier.uri http://hdl.handle.net/10453/17749
dc.description.abstract A new feature description is used for human action representation and recognition. Features are extracted from the Radon transforms of silhouette images. Using the features, key postures are selected. Key postures are combined to construct an action template for each action sequence. Linear Discriminant Analysis (LDA) is applied to obtain low dimensional feature vectors. Different classification methods are used for human action recognition. Experiments are carried out based on a publicly available human action database. en_US
dc.language English en_US
dc.publisher Springer-Verlag Berlin / Heidelberg en_US
dc.relation.isbasedon en_US
dc.title Human Action Recognition Based on Radon Transform en_US
dc.parent Studies in Computational Intelligence vol 346. Multimedia Analysis, Processing and Communications en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation Berlin/Heidelberg en_US
dc.identifier.startpage 369 en_US
dc.identifier.endpage 389 en_US
dc.cauo.name FEIT.School of Computing and Communications en_US
dc.conference Verified OK en_US
dc.for 080100 en_US
dc.personcode 10389219 en_US
dc.personcode 000748 en_US
dc.personcode 990421 en_US
dc.percentage 100 en_US
dc.classification.name Artificial Intelligence and Image Processing en_US
dc.classification.type FOR-08 en_US
dc.edition Studies in Computational Intelligence en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords en_US
dc.staffid 990421 en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record